class_docstr: Main coreference resolution algorithm
docstr: Only resolve coreferences for the mentions in the utterances
  (but use the mentions in previously loaded utterances as possible antecedents)
  Arg:
      utterances : iterator or list of string corresponding to successive utterances
      utterances_speaker : iterator or list of speaker id for each utterance.
          If not provided, assume two speakers speaking alternatively.
          if utterances and utterances_speaker are not of the same length padded with None
      speakers_names : dictionnary of list of acceptable speaker names for each speaker id
  Return:
      clusters of entities with coreference resolved
docstr_tok: ["Only","resolve","coreferences","for","the","mentions","in","the","utterances","(","but","use","the","mentions","in","previously","loaded","utterances","as","possible","antecedents",")","Arg",":","utterances",":","iterator","or","list","of","string","corresponding","to","successive","utterances","utterances_speaker",":","iterator","or","list","of","speaker","id","for","each","utterance",".","If","not","provided",",","assume","two","speakers","speaking","alternatively",".","if","utterances","and","utterances_speaker","are","not","of","the","same","length","padded","with","None","speakers_names",":","dictionnary","of","list","of","acceptable","speaker","names","for","each","speaker","id","Return",":","clusters","of","entities","with","coreference","resolved"]
code: def continuous_coref(
      self, utterances, utterances_speakers_id=None, speakers_names=None
  ):
      """
      Only resolve coreferences for the mentions in the utterances
      (but use the mentions in previously loaded utterances as possible antecedents)
      Arg:
          utterances : iterator or list of string corresponding to successive utterances
          utterances_speaker : iterator or list of speaker id for each utterance.
              If not provided, assume two speakers speaking alternatively.
              if utterances and utterances_speaker are not of the same length padded with None
          speakers_names : dictionnary of list of acceptable speaker names for each speaker id
      Return:
          clusters of entities with coreference resolved
      """
      self.data.add_utterances(
          utterances, utterances_speakers_id, speakers_names
      )
      self.run_coref_on_utterances(
          last_utterances_added=True, follow_chains=True
      )
      return self.get_clusters()
  
imports: import os
  import spacy
  import numpy
  from neuralcoref.train.utils import PACKAGE_DIRECTORY, SIZE_SINGLE_IN
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.document import Document, MENTION_TYPE, NO_COREF_LIST
label_desc: Use image node_id 9 for calling the Coref obj's underlying member method code with example usage: obj.continuous_coref(utterances, utterances_speakers_id, speakers_names) and returns: self